Digital Measurement - How to Evaluate, Track and Measure Marketing Performance

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The presentation discusses the concepts and principles of digital measurement in tracking and measuring marketing performance.

The presentation discusses the concepts and principles of digital measurement in tracking and measuring marketing performance.

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  • 1. >  Digital  Measurement  <   More  than  just  coun.ng  hits!  
  • 2. >  Short  but  sharp  history  §  Datalicious  was  founded  late  2007  §  Strong  Omniture  web  analy.cs  history  §  Now  360  data  agency  with  specialist  team  §  Combina.on  of  analysts  and  developers  §  Carefully  selected  best  of  breed  partners  §  Driving  industry  best  prac.ce  (ADMA)  §  Turning  data  into  ac.onable  insights  §  Execu.ng  smart  data  driven  campaigns  May  2011   ©  Datalicious  Pty  Ltd   2  
  • 3. >  Clients  across  all  industries  May  2011   ©  Datalicious  Pty  Ltd   3  
  • 4. >  Wide  range  of  data  services   Data   Insights   Ac?on   Pla>orms   Analy?cs   Campaigns         Data  collec?on  and  processing   Data  mining  and  modelling   Data  usage  and  applica?on         Web  analy?cs  solu?ons   Customised  dashboards   Marke?ng  automa?on         Omniture,  Google  Analy?cs,  etc   Tableau,  Spo>ire,  SPSS,  etc   Alterian,  SiteCore,  Inxmail,  etc         Tag-­‐less  online  data  capture   Media  aKribu?on  models   Targe?ng  and  merchandising         End-­‐to-­‐end  data  pla>orms   Market  and  compe?tor  trends   Internal  search  op?misa?on         IVR  and  call  center  repor?ng   Social  media  monitoring   CRM  strategy  and  execu?on         Single  customer  view   Customer  profiling   Tes?ng  programs    May  2011   ©  Datalicious  Pty  Ltd   4  
  • 5. >  Smart  data  driven  marke?ng     Metrics  Framework Metrics  Framework Media  AKribu?on Benchmarking  and  trending   Benchmarking  and  trending     Op?mise  channel  mix   Targe?ng     Increase  relevance   Tes?ng   Improve  usability     $$$  May  2011   ©  Datalicious  Pty  Ltd   5  
  • 6. 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Digital  metrics  May  2011   ©  Datalicious  Pty  Ltd   6  
  • 7. >  Digital  data  is  plen?ful  and  cheap      April  2011   ©  Datalicious  Pty  Ltd   7   Source:  Omniture  Summit,  MaS  Belkin,  2007  
  • 8. HITS  How  Idiots  Track  Success  
  • 9. >  Basic  website  metrics  §  Page  view/impression:  The  number  of  .mes  a  page  (an   analyst-­‐definable  unit  of  content)  was  viewed.  §  Visit/session:  A  visit  is  an  interac.on,  by  an  individual,   with  a  website  consis.ng  of  one  or  more  requests  for  an   analyst-­‐definable  unit  of  content  (i.e.  “page  view”).  If  an   individual  has  not  taken  another  ac.on  (typically   addi.onal  page  views)  on  the  site  within  a  specified  .me   period,  the  visit  session  will  terminate.  §  Unique  visitor/browser:  The  number  of  inferred   individual  people  (filtered  for  spiders  and  robots),  within   a  designated  repor.ng  .meframe,  with  ac.vity   consis.ng  of  one  or  more  visits  to  a  site.  Each  individual   is  counted  only  once  in  the  unique  visitor  measure  for   the  repor.ng  period.  May  2011   ©  Datalicious  Pty  Ltd   9   Source:  Web  Analy.cs  Defini.ons,  Web  Analy.cs  Associa.on,  2007  
  • 10. >  Cookie  based  tracking  process     What  if:  Someone  deletes  their  cookies?  Or  uses  a  device   that  does  not  support  JavaScript?  Or  uses  two  computers   (work  vs.  home)?  Or  two  people  use  the  same  computer?  April  2011   ©  Datalicious  Pty  Ltd   10   Source:  Google  Analy.cs,  Jus.n  Cutroni,  2007  
  • 11. >  Unique  visitor  overes?ma?on    The  study  examined    data  from  two  of    the  UK’s  busiest    ecommerce    websites,  ASDA  and  William  Hill.    Given  that  more    than  half  of  all  page    impressions  on  these    sites  are  from  logged-­‐in    users,  they  provided  a  robust    sample  to  compare  IP-­‐based  and  cookie-­‐based  analysis  against.  The  results  were  staggering,  for  example  an  IP-­‐based  approach  overes.mated  visitors  by  up  to  7.6  .mes  whilst  a  cookie-­‐based  approach  overes?mated  visitors  by  up  to  2.3  ?mes.    April  2011   ©  Datalicious  Pty  Ltd   11   Source:  White  Paper,  RedEye,  2007  
  • 12. >  Maximise  iden?fica?on  points    160%  140%  120%  100%   80%   60%   −−−  Probability  of  iden.fica.on  through  Cookies   40%   20%   0   4   8   12   16   20   24   28   32   36   40   44   48   Weeks  April  2011   ©  Datalicious  Pty  Ltd   12  
  • 13. >  Maximise  iden?fica?on  points   Mobile   Home   Work   Online   Phone   Branch  April  2011   ©  Datalicious  Pty  Ltd   13  
  • 14. >  Sample  customer  level  data    April  2011   ©  Datalicious  Pty  Ltd   14  
  • 15. >  Digital  metric  categories   +Social  May  2011   ©  Datalicious  Pty  Ltd   15   Source:  Accuracy  Whitepaper  for  web  analy.cs,  Brian  Clihon,  2008  
  • 16. >  Digital  means  global   “The  image  is  a  model  of  the  Internet,   based  on  how  many  people  view  different   sites  and  how  these  sites  are  related  to   each  other.  There  are  3  colours  on  this   model.  Red,  Green  and  Blue.  Each   represents  users  from  US,  Europe  and  Asia.     The  picture  illustrates  how  non  linear  the   digital  world  is.  It  also  shows  how  some   sites  have  a  strong  centre  of  gravity  for   mass  audiences;  others  have  strong     centres  of  gravity  for  niche  audiences.   It  is  important  to  iden.fy  where  marke.ng   is  going  to  have  most  impact  -­‐  crea.ng   powerful  programs  on  niche  sites,  which   gradually  extend  an  influence  on  the  larger   communi.es;  or  (more  expensive)   marke.ng  ac.vity  on  mass  sites,  that  will   then  generate  a  frenzy  of  interest  in  smaller   niche  groups.”  May  2011   ©  Datalicious  Pty  Ltd   16   Source:  Carat/Isobar,  2007  
  • 17. >  Defining  metrics  frameworks   Media  and  search  data   Website,  call  center  and  retail  data   Reach   Engagement   Ac?on   +Buzz   (Awareness)   (Interest  &  Desire)   (Ac.on)   (Sa.sfac.on)   Quan.ta.ve  and  qualita.ve  research  data   Social  media  data   Social  media  May  2011   ©  Datalicious  Pty  Ltd   17  
  • 18. >  Importance  of  calendar  events     Traffic  spikes  or  other  data  anomalies  without  context  are   very  hard  to  interpret  and  can  render  data  useless  April  2011   ©  Datalicious  Pty  Ltd   18  
  • 19. 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Measuring  reach  May  2011   ©  Datalicious  Pty  Ltd   19  
  • 20. >  Reach  and  channel  overlap     TV/Print     audience   Banner   Search   audience   audience  April  2011   ©  Datalicious  Pty  Ltd   20  
  • 21. >  Ad  server  exposure  test   Banner   TV/Print   Search   Impression   Response   Response   $   Banner   Search   Direct   Impression   Response   Response   $   Users  are   segmented   before  1st   ad  is  even   Exposed  group:  90%  of  users  get  branded  message   served     Control  group:  10%  of  users  get  non-­‐branded  message   Banner   Search   Direct   Impression   Response   Response   $  April  2011   ©  Datalicious  Pty  Ltd   21  
  • 22. >  Indirect  display  impact    April  2011   ©  Datalicious  Pty  Ltd   22  
  • 23. >  Indirect  display  impact    April  2011   ©  Datalicious  Pty  Ltd   23  
  • 24. April  2011   ©  Datalicious  Pty  Ltd   24  
  • 25. >  Indirect  display  impact    April  2011   ©  Datalicious  Pty  Ltd   25  
  • 26. >  New  marketplace:  Search  May  2011   ©  Datalicious  Pty  Ltd   26  
  • 27. >  Google  data  in  Australia     Source:  hSp://www.hitwise.com/au/resources/data-­‐centre  April  2011   ©  Datalicious  Pty  Ltd   27  
  • 28. >  Search  at  all  stages    April  2011   ©  Datalicious  Pty  Ltd   28   Source:  Inside  the  Mind  of  the  Searcher,  Enquiro  2004  
  • 29. >  Search  and  brand  strength    April  2011   ©  Datalicious  Pty  Ltd   29  
  • 30. May  2011   ©  Datalicious  Pty  Ltd   30  
  • 31. >  Search  and  the  product  lifecycle     Nokia  N-­‐Series   Apple  iPhone  April  2011   ©  Datalicious  Pty  Ltd   31  
  • 32. >  Search  and  media  planning    April  2011   ©  Datalicious  Pty  Ltd   32  
  • 33. >  Search  driving  offline  crea?ve    April  2011   ©  Datalicious  Pty  Ltd   33  
  • 34. >  Hitwise  Mosaic  segment  swing  australia.com  vs.  newzealand.com   australia.com  vs.  bulafiji.com     Source:  Hitwise.com.au,  2008  May  2011   ©  Datalicious  Pty  Ltd   34  
  • 35. >  Hitwise  Mosaic  segment  swing  australia.com  vs.  newzealand.com   australia.com  vs.  newzealand.com   Source:  Hitwise.com.au,  2008  May  2011   ©  Datalicious  Pty  Ltd   35  
  • 36. 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Measuring  engagement  May  2011   ©  Datalicious  Pty  Ltd   36  
  • 37. >  Conversion  funnel  1.0   Campaign  responses   Conversion  funnel   Product  page,  add  to  shopping  cart,  view  shopping  cart,   cart  checkout,  payment  details,  shipping  informa.on,   order  confirma.on,  etc   Conversion  event  May  2011   ©  Datalicious  Pty  Ltd   37  
  • 38. >  Conversion  funnel  2.0   Campaign  responses  (inbound  spokes)   Offline  campaigns,  banner  ads,  email  marke.ng,     referrals,  organic  search,  paid  search,     internal  promo.ons,  etc       Landing  page  (hub)       Success  events  (outbound  spokes)   Bounce  rate,  add  to  cart,  cart  checkout,  confirmed  order,     call  back  request,  registra.on,  product  comparison,     product  review,  forward  to  friend,  etc  May  2011   ©  Datalicious  Pty  Ltd   38  
  • 39. >  Addi?onal  success  metrics   Click   Through   $   Click   Add  To   Cart   Through   Cart   Checkout   ?   $   Click   Bounce   Pages  Per   Avg  Cart   Through   Rate   Visit   Value   $   Click   Call  back   Store   Through   requests   Searches   >  ...   $  May  2011   ©  Datalicious  Pty  Ltd   39  
  • 40. May  2011   ©  Datalicious  Pty  Ltd   40  
  • 41. May  2011   ©  Datalicious  Pty  Ltd   41  
  • 42. >  Book:  Tuned  In   “70%  or  more  of  new   products  or  new   product  decisions   were  made  without   market  data”  May  2011   ©  Datalicious  Pty  Ltd   42   Source:  hSp://www.pragma.cmarke.ng.com/tunedin  
  • 43. 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Measuring  ac?on  May  2011   ©  Datalicious  Pty  Ltd   43  
  • 44. >  Key  metrics  by  website  type  May  2011   ©  Datalicious  Pty  Ltd   44   Source:  Omniture  Summit,  MaS  Belkin,  2007  
  • 45. >  Duplica?on  across  channels     Paid     Bid     Search   Mgmt   $   Banner     Ad     Ads   Server   $   Email     Email   Blast   Pla>orm   $   Organic   Google   Search   Analy?cs   $  April  2011   ©  Datalicious  Pty  Ltd   45  
  • 46. >  Cookie  expira?on  impact   Paid     Bid     Search   Mgmt   $   Banner     Banner     Ad     Ad  Click   Ad  View   Server   $   Email     Email   Expira?on   Blast   Pla>orm   $   Organic   Google   Search   Analy?cs   $  April  2011   ©  Datalicious  Pty  Ltd   46  
  • 47. >  De-­‐duplica?on  across  channels     Paid     Search   $   Banner     Ads   $   Central   Analy?cs   Pla>orm   Email     Blast   $   Organic   Search   $  April  2011   ©  Datalicious  Pty  Ltd   47  
  • 48. >  Poten?al  duplica?on  impact    §  Double-­‐coun.ng  of  conversions  across  channels  can   have  a  significant  impact  on  key  metrics,  especially  CPA  §  Example:  Display  ads  and  paid  search   –  Total  media  budget  of  $10,000  of  which  50%  is  spend  on  paid   search  and  50%  on  display  ads   –  Total  of  100  conversions  across  both  channels  with  a  channel   overlap  of  50%,  i.e.  both  channels  claim  100%  of  conversions   based  on  their  own  repor.ng  but  once  de-­‐duplicated  they   each  only  contributed  50%  of  conversions   –  What  are  the  ini.al  CPA  values  and  what  is  the  true  CPA?  §  Solu.on:  $50  ini.al  CPA  and  $100  true  CPA   –  $5,000  /  100  =  $50  ini.al  CPA  and  $5,000  /  50  =  $100  true   CPA  (which  represents  a  100%  increase)  April  2011   ©  Datalicious  Pty  Ltd   48  
  • 49. >  Campaign  flow  and  calls  to  ac?on     =  Paid  media   Organic     PR,  WOM,   search   events,  etc   =  Viral  elements   =  Coupons,  surveys   YouTube,     Home  pages,   Paid     TV,  print,     blog,  etc   portals,  etc   search   radio,  etc   Direct  mail,     Landing  pages,   Display  ads,   email,  etc   offers,  etc   affiliates,  etc   C1   C2   CRM   Facebook   program   TwiKer,  etc   C3   POS  kiosks,   Call  center,     loyalty  cards,  etc   retail  stores,  etc  April  2011   ©  Datalicious  Pty  Ltd   49  
  • 50. >  Success  aKribu?on  models   Banner     Paid     Organic   Success   Last  channel   Search   Ad   Search   $100   $100   gets  all  credit   Banner     Paid     Email     Success   First  channel   Ad   $100   Search   Blast   $100   gets  all  credit   Paid     Banner     Affiliate     Success   All  channels  get   Search   Ad   Referral   $100   $100   $100   $100   equal  credit   Print     Social     Paid     Success   All  channels  get   Ad   Media   Search   $33   $33   $33   $100   par?al  credit  May  2011   ©  Datalicious  Pty  Ltd   50  
  • 51. >  First  and  last  click  aKribu?on     Chart  shows   percentage  of   channel  touch   points  that  lead   Paid/Organic  Search   to  a  conversion.   Neither  first     Emails/Shopping  Engines   nor  last-­‐click   measurement   would  provide   true  picture    April  2011   ©  Datalicious  Pty  Ltd   51  
  • 52. >  Full  path  to  purchase   Introducer   Influencer   Influencer   Closer   $   SEM   Banner   Direct     SEO   Online   Generic   Click   Visit   Branded   Banner     SEO   Affiliate   Social   Offline   View   Generic   Click   Media   TV     SEO   Direct     Email   Abandon   Ad   Branded   Visit   Update  April  2011   ©  Datalicious  Pty  Ltd   52  
  • 53. >  Search  call  to  ac?on  for  offline    April  2011   ©  Datalicious  Pty  Ltd   53  
  • 54. April  2011   ©  Datalicious  Pty  Ltd   54  
  • 55. >  Research  online  buy  in  store  May  2011   ©  Datalicious  Pty  Ltd   55   Source:  2008  Digital  Future  Report,  Surveying  The  Digital  Future,  Year  Seven,  USC  Annenberg  School  
  • 56. >  Store  locator  searches  May  2011   ©  Datalicious  Pty  Ltd   56  
  • 57. >  Offline  sales  driven  by  online   Adver?sing     Phone   Credit  check,   campaign   order   fulfilment   Retail   Confirma?on   order   email   Website   Online   Online  order   Virtual  order   research   order   confirma?on   confirma?on   Cookie  April  2011   ©  Datalicious  Pty  Ltd   57  
  • 58. How  many  survey  responses  do  you  need     if  you  have  10,000  customers?   How  many  email  opens  do  you  need  to  test  2  subject  lines   if  your  subscriber  base  is  50,000?   How  many  orders  do  you  need  to  test  6  banner  execu?ons     if  you  serve  1,000,000  banners  April  2011   ©  Datalicious  Pty  Ltd   58   Google  “nss  sample  size  calculator”  
  • 59. How  many  survey  responses  do  you  need     if  you  have  10,000  customers?   369  for  each  ques?on  or  369  complete  responses   How  many  email  opens  do  you  need  to  test  2  subject  lines   if  your  subscriber  base  is  50,000?  And  email  sends?   381  per  subject  line  or  381  x  2  =  762  email  opens   How  many  orders  do  you  need  to  test  6  banner  execu?ons     if  you  serve  1,000,000  banners?   383  sales  per  banner  execu?on  or  383  x  6  =  2,298  sales  April  2011   ©  Datalicious  Pty  Ltd   59   Google  “nss  sample  size  calculator”  
  • 60. >  Addi?onal  success  metrics     Click   Through   $   Click   Add  To     Cart   Through   Cart   Checkout   ?   $   Click   Page   Page     Product     Through   Bounce   Views   Views   $   Click   Call  back   Store   Through   request   Search   ?   $  April  2011   ©  Datalicious  Pty  Ltd   60  
  • 61. 101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010  >  Measuring  buzz  May  2011   ©  Datalicious  Pty  Ltd   61  
  • 62. >  Importance  of  social  media     Search   Company   Promo?on   Consumer   WOM,  blogs,  reviews,   ra?ngs,  communi?es,   social  networks,  photo   sharing,  video  sharing  May  2011   ©  Datalicious  Pty  Ltd   62  
  • 63. >  Measuring  social  media     Sen.ment   Influence   Reach  April  2011   ©  Datalicious  Pty  Ltd   63  
  • 64. May  2011   ©  Datalicious  Pty  Ltd   64  
  • 65. Sen?ment  analysis:  People  vs.  machine   April  2011   ©  Datalicious  Pty  Ltd   65  
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